Recently there has been increased commercial as well as academic interest in the area of so called “condition based” machine maintenance.1,2,3 Effective solutions to machine maintenance can eliminate causes of machine downtime caused by abrupt failures of components. Predictive maintenance can, to some extent, eliminate abrupt downtimes but, unless the root cause of the failure is discovered and eliminated, predictive maintenance does not adequately address the failure of machine replacement parts, which fail randomly. 1 IEEE TRANSACTIONS ON ENERGY CONVERSION, VOL. 20, NO. 4, DECEMBER 2005 719 Condition Monitoring and Fault Diagnosis of Electrical Motors—A Review2 Signal Processing, Communication, Power and Embedded System (SCOPES), 2016 International Conference: Condition monitoring of induction motors:—A review3 U.S. Pat. No. 6,738,748 B2
It is generally accepted that there are two major root causes of early machine failures. One of these causes is improper operation, for example, operating a machine without changing an oil or air filter, oil, lubricating grease, and the like, which may lead to abnormal vibration. Similarly, bad operation embraces instances where a machine is made to work beyond its specified maximum speed or loading, or in temperatures above those for which the machine was designed to operate, or with voltage or current outside of the machine's design requirements.
A second major cause of early machine failure is poor quality of incoming electrical power. In the case of three-phase electrical power, such poor quality can be manifested by high phase imbalance of both current and voltage, presence of higher harmonics of both current and voltage, and low noise ratio typically due to poor grounding. Any such poor quality parameters present in the power provided to a machine accelerates failure of motor stators and rotor bearings due to excessive thermal and electrical stresses.
Some investigators have endeavored to understand the predictive nature of machine failures, especially for turbomachinery, namely machinery having rotating elements, such as vacuum pumps, jet engines, electrical generators, electric motors, and the like.
Elimination of the root cause of failures of these machines using predictive engines, built from predictive, preventive, and root cause discovery of vibration and power analysis, using machine wearable sensors, has not been effectively developed heretofore.4,5,6 There has been some study of root cause of failures caused by poor electrical power quality. The effect of higher harmonics and phase imbalance of both current and voltage on machine health has been subject to some academic and commercial research, but actively correlating the root causes of machine degradation, namely bearing or shaft misalignment in a turbomachine, with power quality, has not been effectively studied and is not widely understood. 7,8,9 4 Harmonics and Quality of Power, 2000. Proceedings. Ninth International Conference on: Induction motors loss of life due to voltage imbalance and harmonics: a preliminary study5 Electrical Machines (ICEM), 2014 International Conference: Evolution of high order fault harmonics during a bar breakage with compensation6 Systems, Signal Processing and their Applications (WoSSPA), 2013 8th International Workshop: Fault detection and diagnosis in rotating machinery by vibration monitoring using FFT and Wavelet techniques7 Harmonics and Quality of Power, 2000. Proceedings. Ninth International Conference on: Induction motors loss of life due to voltage imbalance and harmonics: a preliminary study8 Electrical Machines (ICEM), 2014 International Conference: Evolution of high order fault harmonics during a bar breakage with compensation9 Systems, Signal Processing and their Applications (WoSSPA), 2013 8th International Workshop: Fault detection and diagnosis in rotating machinery by vibration monitoring using FFT and Wavelet techniques
In factories, direct current and vector current drives generate alarming levels of high harmonics throughout the electrical power distribution line unless filtered by isolators or harmonic filters.10 Even if an Internet of Things based predictive or condition based maintenance system is present in a factory with turbomachinery, motors continue to degrade at an accelerated pace until the root cause of the harmonics is found and eliminated. Predictive maintenance can, at best, help to avoid abrupt breakdowns but cannot address the issue of reduced lifespan of turbomachines resulting from faster degeneration of motor cores burned by higher harmonics generated from DC and vector current voltage drives. 10 Protective Relay Engineers, 2013 66th Annual Conference: Challenges and solutions of protecting variable speed drive motors
Since electrical line issues tend to be local and transient, and effect only the machines connected to the same line or to the same electrical distribution panel, it is important that predictive maintenance data obtained from a machine and electrical line conditions be correlated in a local server so that latency in receiving them does not hamper effective and quick decision making. For this reason, effective computation is done in an edge device, sometimes also called a fog device and in an edge cloud, which is a mini-server connected to the same net as a fog device.